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Embracing a pattern of change: Model Innovation across banking, insurance and asset management

“This is a world of six-month product development cycles and constant updates, primarily of software, with a huge premium on simple user interfaces and trusted security.”

“This is a world of six-month product development cycles and constant updates, primarily of software, with a huge premium on simple user interfaces and trusted security.”

These are the words of Christine Lagarde, managing director of the international monetary fund (IMF) in a 2017 speech at a Bank of England conference in London. She was outlining her vision of the financial services sector in the year 2040. She adds this is “a world where data is king. A world of many new players without imposing branch offices.”

Virtual currencies, she envisaged, will have a big role to play, becoming easier, safer and largely more stable than existing currencies. Artificial intelligence, meanwhile, will be adept at slicing and dicing big data, she said, “assisting policy-makers, offering real-time forecasts, spotting bubbles, and uncovering complex macro-financial links.”

New models of financial intermediation appear to emerge, she added, with the potential to trigger a break-up or unbundling of financial services as customers know them today.

Alongside new players will be new business models. In the first two articles in this series, we focused on how technology change and regulatory change are reshaping financial services. In this article, we focus on how new business models are emerging.

“I’m seeing more change during the last two years than I did in the previous ten years. It’s a ‘must’ to transform–not just to improve, but to really transform,” says Vincent Bastid, CEO of Efma, the European Financial Management and Marketing Association.

As we will see, business model change is playing out at different rates and in different ways across the three key pillars of financial services: banking, asset management, and insurance.

Banking unbundled

Perhaps one of the most significant business model shifts on the horizon is in retail banking, with the emergence of ‘open banking’. Institutions in Europe, in particular, are racing to be ready for the introduction of the EU’s Payment Services Directive (PSD2) in January 2018.

PSD2 will require retail banks to provide third-party providers–from young fintech start-ups to technology giants such as Apple and Amazon–access to their customers’ online accounts through open application programming interfaces (APIs), where account holders have provided consent to for them to do so. That, in turn, will enable customers to access services from these providers, direct from their bank accounts–price comparison apps for mortgages, for example, or services that help them to manage household budgets better.

In the UK, HSBC was the first to publish an open banking API in September 2017, and it has already built a new mobile banking app to test out some of the features that open banking promises to bring. Some of the features of this HSBC Beta app include Safe Balance, which shows customers how much disposable income they have before their next payday, and a Spend Analysis tool, which categorises spending and analyses patterns for more informed financial decision making. In time, HSBC customers will be able to open up this data to third-party providers.

Beyond Europe, too, there’s a lot of discussion about open banking. The Monetary Authority of Singapore (MAS), for example, is enthusiastically pushing financial institutions to adopt APIs, and is leading by example by publishing its own APIs online. And in its 2017/18 budget, the Australian government announced its intentions to introduce an open banking regime, with Macquarie Bank the first to act, launching its own open banking platform in September 2017.

In capital markets, business model change is also underway, not least because of pressures on margins and competition from fintech start-ups. Take, for example, algorithmic trading: this uses advanced algorithms to identify optimal trading strategies and speed up transactions in financial markets. All this gets automated by machines–often at the expense of human jobs. Equities trading has been hardest hit here, but many believe that fixed income, currencies and commodities trading jobs are likely to follow.

The rise of algo trading, as it is known, has been fuelled by both technology and regulatory change. On the technology front, the processing power required to perform this kind of rules-based work has never been cheaper. On the regulatory front, capital requirements laid out in Basel III, for example, and the Volker rule, which prohibits banks from conducting certain investment activities with their own accounts, mean that machines that are programmed to observe and comply with clearly defined rules when it comes to trading make good sense.

Blockchain technology is also likely to have a big impact. Used to create tamper-proof, cryptographically secure distributed ledgers of transactions, it offers a faster and more cost-effective alternative to the traditional clearing and settlement mechanisms on which financial services companies have traditionally relied. That, in turn, could spell disruption for many back office jobs.

However, if old jobs disappear, new one will emerge. In June, the Financial Times reported that blockchain-related jobs had trebled in the past year, as financial services scrambled to recruit the expertise they’ll need to harness the technology. Similarly, in algorithmic trading, human talent is needed to develop and train algorithms–another rich source of employment opportunities for those with these sought-after skills. In other words, financial institutions in the future will rely far more on IT and regulatory experts that can get systems up and running that create new efficiencies and less on administrative staff to handle routine tasks that machines can perform faster and more cost-effectively.

The pressure from new entrants, meanwhile, is relentless. These companies attracted some 216 funding deals worth US$1.89bn in 2016, notes research firm CB Insights. They include Clearpool in hedge fund management, Peernova in clearance and settlement and Ayadasi in risk and compliance.

This puts established providers under pressure, of course, but many are rising to the challenge, says Mr Bastid of Efma. “There is a lot of talk about fintech, of course, but when people say that the established banks are behind, that they don’t innovate–well, it’s simply not true.” Some of the most disruptive new business models could come from the banks themselves, he argues, and many will increasingly derive from R&D-focused tie-ups between established providers and new entrants.

Investing in new investment models

In asset management, automation is also a key theme, with the rise of so-called ‘robo advisors’.

These could hold the key to many of the challenges faced by the sector, according to a 2016 report from executive search firm Russell Reynolds. “A near-perfect storm of poor investment performance, mutual fund outflows, investor preferences for passive, low-fee strategies, and an onerous regulatory environment have led to a fundamental shift in the asset management business model,” they write.

“From the largest traditional asset managers to the smallest alternative and wealth management firms, assets under management have been contracting and/or moving into lower-margin products, forcing these firms to reassess their revenue, growth and profit potential going forward.”

In particular, the authors point to an emerging demographic of younger and more digitally oriented investors, who are focused “as much on fees as they are on performance.”

This hardly comes as news to Jon Stein, CEO of Betterment, one of a new breed of asset management firms, along with Wealthfront and Acorns, that aims to give investors new, digitally enabled options for growing their wealth.

A long-time advisor to Wall Street businesses, Stein says he weighed up his options carefully before settling on asset management as his target back in 2008. Banking, he felt, was too complex, and payments were already being addressed by other new players in the market. But asset management, he felt, presented fertile ground for “doing things better, for rethinking things from the customer’s perspective”, in his words.

It was “slowing going” at first, says Stein, but today Betterment boasts around $10bn in assets under management, on behalf of some 275,000 customers. Artificial intelligence (AI) plays a big part in automating the process of helping Betterment customers manage their portfolios, and that helps to drive down costs, but while the company is often referred to as a ‘robo advisor’, Stein is keen to point out that Betterment still retains the human touch, by employing in-house investment advisors and customer service staff to consult with clients.

He claims that the whole asset management industry is now fundamentally changing and moving in a similar, digital direction–and there is plenty of evidence that this is the case. Charles Schwab and Vanguard have launched their own robo advisor platforms; UBS and Wells Fargo are partnering with online financial advisor SigFig Wealth; and BlackRock acquired FutureAdvisor, another online advisor, back in 2015.

And in a sign of convergence between new and old, Betterment announced in September 2017 that it is to partner with BlackRock and Goldman Sachs to offer its customers a wider range of portfolio options. A smart-beta portfolio option managed by Goldman Sachs will give users exposure to riskier investment areas, such as emerging markets and US small-capitalisation companies, while an income-based portfolio managed by BlackRock will target risk-averse investors seeking higher returns.

Insurance pivots innovation towards risk prevention

At a July 2017 insurance conference in South Africa, Allianz chief executive Oliver Bäte spoke of the “profound transformation” that digitalisation is driving in a staid, conservative sector. Customers, he said, now choose an insurance product “primarily because it’s easy to use, transparent in terms of price and quality, and personalised–and because it’s available to them via the digital channels they want to buy it from.”

Allianz, a 127-year old company, is on a mission to make its business model “digital by default” and has announced it is to spend more than US$800m annually in pursuit of that goal. Rivals are following suit. At the UK’s Aviva, for example, CEO Mark Wilson has said the company is spending £100m (US$132m) annually on digital transformation.

This is likely to play out for customers in many different ways, according to the type of insurance they need. But the main themes centre on using digital technologies to help customers buy insurance, to ask for advice and to submit claims in faster, more convenient ways. And behind the scenes, these technologies are helping to more accurately assess risk, offer more personalised pricing to customers based on their individual claims histories and process claims faster.

Munich Re, for example, has developed a ‘Digital Doctor’ app for health insurance customers. This takes the form of an intelligent questionnaire, based on algorithms, which asks for details of the user’s symptoms to build a picture of their condition. Once the data has been analysed, a doctor can provide the customer with medical advice by phone, live video or chat messages and, if necessary, refer them to a specialist from the insurer’s pool of clinicians.

But digitalisation of the relationship between an insurance company and its customer is only one part of the puzzle. There is also a fundamental shift in the way that back-office work is performed to consider, too.

If underwriting today is plagued by too much admin and too much searching for information, technology looks set to change all that. Traditionally, the role of the underwriter has been one of the most important roles in the insurance business, but as more information is held on machines, and less on paper, it makes more sense to have computers trawl through that information, picking out relevant records and data, and identifying trends and patterns, using artificial intelligence and machine learning.

Data coming from sensors in machines and buildings is also becoming more important, too, giving underwriters valuable clues into aspects of risk that they might not have previously considered. A smart building, for example, or a small aircraft has the ability to convey a great deal of information about its status, performance and condition. This information can help underwriters better understand the risks they face and, in the event of an insurance claim, tell the insurance company more about the events leading up to loss or damage. In this way, the business of insurance providers is likely to move away from simply shouldering risk in return for payment, in favour of a risk-prevention model based on a deep understanding of how an insured asset is used and maintained.

Conclusion

In recent years, technology change and regulatory change have descended on the financial services industry and forced profound business model change–and it’s a pattern that looks set to continue.

The financial crisis of 2008 onwards may have dented consumer confidence in the industry, prompting new waves of regulation–but today, new rules and new technologies make it possible to deliver financial service in new and often better ways that could go a long way to restoring that faith.

“Banks are very aware that they need to prepare to match new expectations. They know that they need to go beyond what they’ve done in the past and make new alliances. It just takes a new mindset and flexibility will be key to that,” says Mr Bastid of EFMA.

Becca is an editor for The Economist Intelligence Unit's thought leadership division in the Americas. She specialises in financial market topics. Prior to joining The Economist Group’s Content Solutions Unit (CSU), Becca worked in a senior editorial role at Wall Street & Technology where she reported on all aspects at the intersection of capital markets, investment management and information technology. She has extensive experience covering big data, data security, mobility, enterprise technology, and the impact of regulations and social media on business strategy.

Becca has also held project management, content marketing, and business development roles at a startup brokerage firm, and regularly reported on the US stock market and trading strategies. She is a graduate of New York University with a dual bachelor’s degree in both economics and environmental studies.

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